🇳🇬 Outbreak Investigation of Acute Ascites
  • Overview
  • Case description
  • Exposures
  • Cases distribution in 🇳🇬 by State
  • Cases distribution in 🇳🇬 by Province (Sokoto)
  • 📈 Cases per week and sex
  • 📈 Cases vs Controls per week
  • Age and Sex Distribution
  • Digestive Symptoms by Age
  • Digestive symptoms - Cases vs Controls
  • Demographics - Cases vs Controls
  • Reported Symptoms - Cases vs Controls
Variable

cases
N = 123

controls
N = 264

p-value 1
Age, n (%)

0.029
    7-27 days 0 (0%) 2 (0.8%)
    1-4 years 29 (24%) 33 (13%)
    5-9 years 54 (44%) 121 (46%)
    10-14 years 40 (33%) 108 (41%)
Sex, n (%)

0.4
    Male 67 (54%) 161 (61%)
    Female 56 (46%) 102 (39%)
    Unknown 0 (0%) 1 (0.4%)
1

Fisher’s exact test

Variable

cases
N = 123

controls
N = 264

p-value

1
Abdominal distention, n (%) 55 (96%) 4 (100%) >0.9
    Missing/Unknown 66 260
Abdominal pain, n (%) 53 (95%) 4 (100%) >0.9
    Missing/Unknown 67 260
Wheeze, n (%) 4 (80%) 0 (NA%)
    Missing/Unknown 118 264
Cough, n (%) 3 (60%) 0 (NA%)
    Missing/Unknown 118 264
Vomiting, n (%) 26 (46%) 4 (100%) 0.11
    Missing/Unknown 67 260
Loss of appetite, n (%) 21 (38%) 0 (0%) 0.3
    Missing/Unknown 67 260
Diarrhoea, n (%) 16 (30%) 4 (100%) 0.011
    Missing/Unknown 69 260
...with sputum, n (%) 1 (33%) 0 (NA%)
    Missing/Unknown 120 264
Any problem of gastrointestinal tract, n (%) 55 (45%) 4 (1.8%) <0.001
    Missing/Unknown 0 37
Fever, n (%) 27 (22%) 8 (3.3%) <0.001
    Missing/Unknown 0 19
Blood in stool, n (%) 2 (3.6%) 0 (0%) >0.9
    Missing/Unknown 68 260
Sweating or chills (day or night), n (%) 3 (2.5%) 5 (2.2%) >0.9
    Missing/Unknown 3 34
Any chest problem, n (%) 5 (4.1%) 2 (0.9%) 0.049
    Missing/Unknown 2 32
Excessive salivation, n (%) 1 (1.9%) 0 (0%) >0.9
    Missing/Unknown 69 260
Pale stool, n (%) 1 (1.8%) 0 (0%) >0.9
    Missing/Unknown 68 260
Any ear, nose or throat problem, n (%) 1 (0.8%) 0 (0%) 0.3
    Missing/Unknown 3 35
Any muscle or bone problem, n (%) 1 (0.8%) 0 (0%) 0.3
    Missing/Unknown 3 34

Only exposures with non-zero prevalence are shown.

1

Fisher’s exact test; Pearson’s Chi-squared test

Antibiotics use

25%
  • Reported Symptoms
  • Medical conditions
  • Vaccination
Variable Prevalence Percentage Frequency
Any problem of gastrointestinal tract 45
60.8%
45 / 74
Abdominal distention 45
97.8%
45 / 46
Abdominal pain 42
93.3%
42 / 45
Vomiting 23
51.1%
23 / 45
Fever 22
29.7%
22 / 74
Loss of appetite 19
42.2%
19 / 45
Diarrhoea 15
33.3%
15 / 45
Any chest problem 4
5.4%
4 / 74
Wheeze 3
75%
3 / 4
Sweating or chills (day or night) 2
2.7%
2 / 74
Blood in stool 2
4.4%
2 / 45
Cough 2
50%
2 / 4
Breathlessness 2
100%
2 / 2
Pale stool 1
2.2%
1 / 45
Excessive salivation 1
2.2%
1 / 45
Any muscle or bone problem 1
1.4%
1 / 74
Any ear, nose or throat problem 1
1.4%
1 / 74
...with sputum 1
50%
1 / 2
Pain in mouth 1
100%
1 / 1
Runny nose 1
100%
1 / 1
Swallowing problem 1
100%
1 / 1
Difficult swallow 1
100%
1 / 1
Painful swallow 1
100%
1 / 1
Fatigue or malaise 1
100%
1 / 1
Muscle pain or aching 1
100%
1 / 1
.. duration 0
0%
0 / 45
Any neurological problems 0
0%
0 / 74
Any eye problem 0
0%
0 / 74
...with blood 0
0%
0 / 24
Altered level of consciousness 0
0%
0 / 2
Seizures 0
0%
0 / 1
Pain or redness in the eye 0
0%
0 / 1
Sore throat 0
0%
0 / 1
Muscle cramps 0
0%
0 / 1
Variable Prevalence Percentage Frequency
Chronic heart disease 1
0.5%
1 / 182
Chronic lung disease 1
0.5%
1 / 183
Chronic neurologic condition 1
0.5%
1 / 184
Tuberculosis (active) 1
0.5%
1 / 183
Congenital anomaly 0
0%
0 / 178
Chronic liver disease 0
0%
0 / 182
Chronic kidney disease 0
0%
0 / 182
Diabetes 0
0%
0 / 183
Hematological Disorders 0
0%
0 / 182
HIV 0
0%
0 / 182
Cancer 0
0%
0 / 183
Other immunosuppressive condition 0
0%
0 / 184
Variable Prevalence Percentage Frequency
BCG 16
8.6%
16 / 187
Yellow fever 13
7%
13 / 187
IPV 11
5.9%
11 / 187
Hepatitis B vaccine 7
3.7%
7 / 187
Rotavirus 7
3.7%
7 / 187
Mumps and Rubella (MMR) 6
3.2%
6 / 187
Hepatitis A vaccine 4
2.1%
4 / 187
  • Food exposures prior to hospital admission - Cases
  • Food exposures prior to hospital admission - Controls
  • Exposure to medication prior to hospital admission - Cases vs Controls
  • Other exposures prior to hospital admission - Cases vs Controls

Variable

cases
N = 123

controls
N = 264

p-value

1
Antibiotics, n (%) 66 (55%) 2 (0.8%) <0.001
    Missing/Unknown 3 0
Paracetamol/acetaminophen, n (%) 11 (9.0%) 1 (0.4%) <0.001
    Missing/Unknown 1 0
Other medications, n (%) 6 (4.9%) 0 (0%) <0.001
    Missing/Unknown 1 0
Cough Medicine, n (%) 2 (1.6%) 0 (0%) 0.10
    Missing/Unknown 1 2

Only exposures with non-zero prevalence are shown.

1

Pearson’s Chi-squared test; Fisher’s exact test

Variable

cases
N = 123

controls
N = 264

p-value

1
Access to a latrine or toilet, n (%) 117 (99%) 222 (93%) 0.011
    Missing/Unknown 5 25
Does the patient frequently handle or come in contact with soil or sand?, n (%) 75 (65%) 50 (25%) <0.001
    Missing/Unknown 7 65
Any outbreaks reported by school or day care prior to symptom onset, n (%) 3 (30%) 1 (33%) >0.9
    Missing/Unknown 113 261
Do you keep any animals as pets or domestic animals, n (%) 32 (27%) 42 (20%) 0.2
    Missing/Unknown 3 56
Any new illnesses or infections in household members or other close contacts prior to symptom onset, n (%) 13 (11%) 8 (3.7%) 0.010
    Missing/Unknown 2 48
Any contact with wild animals at the time of the illness, n (%) 13 (11%) 1 (0.5%) <0.001
    Missing/Unknown 7 51
Attendance to in-person school or day care prior to symptom onset, n (%) 10 (8.5%) 3 (1.4%) 0.003
    Missing/Unknown 5 52
Does anyone smoke cigarettes or tobacco inside any building where you work or spend other time?, n (%) 7 (6.0%) 4 (2.1%) 0.11
    Missing/Unknown 6 72
Any contact with stray animals, n (%) 8 (6.7%) 1 (0.5%) 0.002
    Missing/Unknown 3 51
Does anyone smoke cigarettes or tobacco inside the building where you sleep (do not include yourself)?, n (%) 3 (2.6%) 3 (1.5%) 0.7
    Missing/Unknown 7 69
Any animal bite/scracth prior to symptoms onset, n (%) 2 (1.7%) 0 (0%) 0.12
    Missing/Unknown 5 49

Only exposures with non-zero prevalence are shown.

1

Pearson’s Chi-squared test; Fisher’s exact test

  • Exposure to medication prior to hospital admission
  • Other exposures prior to hospital admission
Variable Prevalence Percentage Frequency
Antibiotics 42
22.5%
42 / 187
Paracetamol/acetaminophen 8
4.3%
8 / 187
Other medications 4
2.1%
4 / 187
Cough Medicine 1
0.5%
1 / 187
Allergy medicine 0
0%
0 / 187
Aspirin 0
0%
0 / 187
Ibuprofen 0
0%
0 / 187
Herbal medicine/naturopathic/homeopathic medicine 0
0%
0 / 187
Variable Prevalence Percentage Frequency
Access to a latrine or toilet 96
51.3%
96 / 187
Does the patient frequently handle or come in contact with soil or sand? 57
30.5%
57 / 187
Do you keep any animals as pets or domestic animals 30
16%
30 / 187
Any new illnesses or infections in household members or other close contacts prior to symptom onset 15
8%
15 / 187
Any contact with wild animals at the time of the illness 12
6.4%
12 / 187
Attendance to in-person school or day care prior to symptom onset 10
5.3%
10 / 187
Does anyone smoke cigarettes or tobacco inside any building where you work or spend other time? 6
3.2%
6 / 187
Any contact with stray animals 5
2.7%
5 / 187
Did the patient or household member start using any new personal care products (e.g. soaps, lotions) prior to symptom onset? 4
2.1%
4 / 187
Any outbreaks reported by school or day care prior to symptom onset 3
30%
3 / 10
Any problem or exposure to different water prior to symptom onset 2
1.1%
2 / 187
Does anyone smoke cigarettes or tobacco inside the building where you sleep (do not include yourself)? 2
1.1%
2 / 187
Any animal bite/scracth prior to symptoms onset 2
1.1%
2 / 187
Any national or overseas trip prior to symptom onset 1
0.5%
1 / 187
  • Antibiotics exposure
  • Pets/domestic animals exposure
  • Type of latrine or toilet


This dashboard displays statistics of reported cases of ascites in 🇳🇬 as of 2025-05-28

Total cases 187
Total controls 422
Female cases 41%
Persons with HIV 0
Below 5 yrs 25%

Disclaimer

Data are provided by many contributors through the the WHO Clinical data platform and are not necessarily representative. To become a contributor, please see the terms of use and register here.